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Monthly Maintenance on July 2

posted on June 30, 2014 On Wednesday, July 2, from 04:00 - 15:00, MSI staff will perform scheduled maintenance and upgrades to the network and various systems. During this maintenance period, we will be performing the following updates: • The MSI central filesystem, Panasas, will be upgraded to the...

Creating Realistic Animations of Nature

One of the most exciting areas that researchers use MSI for is computer-generated visualizations. Avery Musbach, a graduate student in the Department of Computer Science and Engineering , is the lead author on a paper that demonstrates the power of scientific computing to create visualizations. The...

Genomics, Metagenomics, and Transcriptomics of Fungal Pathogens of Invertebrates

Abstract: 

Genomics, Metagenomics, and Transcriptomics of Fungal Pathogens of Invertebrates

Using a combination of next generation sequencing, phylogenomics, genetics, and natural products chemistry, the Bushley lab examines the evolution, diversity, and functions of fungal secondary metabolites. Current research projects utilizing MSI resources include: 

  • A comparative population genomic study of the evolution of NRPS secondary metabolites among strains of the beetle pathogen and cyclosporin producing fungus Tolypocladium inflatum using PacBio sequencing
  • A comparative genomic and transcriptomic analysis of interactions of insect pathogenic and endophytic fungi with both plant and insect hosts
  • A metagenomics study of fungal pathogens of the  soybean cyst nematodes to elucidate patterns of distribution in natural and agricultural ecosystems and potential roles in mediating resistance to nematodes
  • Metagenomics analyses of tropical endophytic fungi of Papua New Guinea and potential anti-herbivore and anti-cancer activity.

These research projects utilize HPC computing for de-novo genome sequencing and assembly, RNA-Seq, network analysis, large-scale phylogenomic analyses, and population genotyping.

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Group name: 
bushleyk

Hydrological Modeling

Abstract: 

Hydrological Modeling

This group uses different computational models to investigate connections between the hydrological cycle and other aspects of the environment.  Current projects mainly employ two different models. The first is the reactive-transport model PHT3D, which couples the groundwater model MODFLOW with the transport model MT3DMS and geochemical model PHREEQC. The researchers are using PHT3D in a study investigating the influence of groundwater on how sulfate loading in Minnesota streams and lakes may be affecting wild rice. Simulations represent multiple geochemical components that interact through many coupled reactions and complex flow in a 2D to 3D domain, thus requiring significant computational resources for model testing and calibration. The group is also using PHT3D to model sulfate release from taconite mining basins to surrounding groundwater and surface water systems. Plans for arsenic modeling based on new chemical analytical data are also in place for 2016.

The second main model used by this group is the Community Land Model (CLM), which is the land-surface model component in NCAR's Community Earth System (CESM). This model will be implemented statewide over Minnesota to assess how changing vegetation conditions impact groundwater recharge. A major task will be to condition the model on satellite observations of vegetation conditions and groundwater level data from the state's observation well network. Conditioning the model requires ensemble simulations over the entire state that must be carried out on an HPC system.

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Group name: 
ngg

High-Performance and Big Data Research

Abstract: 

High-Performance and Big Data Research

This group's research during 2015 focused on the development of parallel shared-memory graph partitioning, ordering, and clustering algorithms that use the multilevel paradigm. Graph partitioning is used widely for parallel task scheduling and data distribution. Graph ordering is used reducing the amount of computation and memory required for sparse direct numerical methods. Graph clustering is a widely used technique for discovering relationships between data points by creating groups of unconstrained size with high internal connectivity. Access to MSI's HPC resources has been critical in the development of these algorithms as evaluating the scalability of the algorithms requires machines with a large number of compute cores, and many of the graphs/matrices in these domains reach massive size, requiring large amounts of memory.

The group's work in 2016 focuses on developing hybrid shared/distributed memory codes that can effectively utilize compute architectures composed of many multicore nodes. This work will be an extension of the researchers' past work on shared and distributed memory graph partitioning, ordering, and clustering. Part of this will include ensuring their methods scale to very large numbers of processing cores. These methods will be required for partitioning, ordering, and clustering problems on the next generation of large petascale and exascale machines, which will have millions of processing cores.

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Group name: 
karypisg

LATIS: Supporting Research Computing in the Liberal Arts

Abstract: 

LATIS: Supporting Research Computing in the Liberal Arts

The Liberal Arts Techologies and Innovation Services (LATIS) works to enhance research and scholarship by integrating appropriate technologies into the workflow of faculty, staff, and students. While LATIS is well positioned within the College of Liberal Arts (CLA) to provide the resources, tools, and expertise over infrastructure and software engineering, pedagogy, media, and social science research methods, their mandate is much broader. They strive to engage the broader scientific community in the issues that face the liberal arts, and they encourage their users to view their compute- and data-intensive tasks not only as as an integral component of their study design, but one that could benefit from communities outside of their own.

Part of this challenge is to convince CLA scholars to view their questions in the light of what HPC can offer, and when appropriate, to bring in the the resources MSI has at its disposal. Accordingly, this Principal Investigator uses MSI access to keeping abreast of the technologies and software MSI supports, to design proof-of-concepts directly on MSI's infrastructure, to consult with CLA clients on the appropriate use of MSI resources, and to make the transition between LATIS environments and MSI environments as clean as possible.

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Group name: 
olsend2

Geomicrobiology Lab

Abstract: 

Geomicrobiology Lab

The overall goal of research in the Santelli Geomicrobiology Lab is to examine interactions between minerals and microorganisms, including fungi, to understand how biomineralization, biocorrosion, and metabolic activity influence the fate and distribution of metals, nutrients, and pollutants in the environment. The lab's specific research objectives are driven by conducting fundamental scientific research on environmentally relevant biogeochemical processes and key elements in nature that are further influenced by anthropogenic activities, such as mining and agriculture. In addition to answering key questions on the mechanisms, metabolic pathways, and geochemical impact of mineral-microbe interactions, the researchers seek to inform and improve strategies for remediating inorganic pollutants to improve the quality and health of water and soil environments.

The group is using MSI’s HPC resources for analysis of large quantities of DNA sequences using a variety of software packages. Current and near future work will include whole genome assembly of fungal genomes, RNAseq analysis, microbiome, and metagenomics analysis. The group is also storing sequence data for numerous fungal genomes.

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Group name: 
santelli

February 2017 Maintenance

On Wednesday, February 1, 2017, from 8am - 4pm CDT, MSI staff will perform scheduled maintenance and upgrades to the network and various MSI systems. During this month's scheduled maintenance period, MSI will apply updates to prevent jobs from using more memory or CPU resources than what the job...

This two part tutorial will first introduce you to the concept of interactive high performance computing, as distinct from batch computing. We will cover the Citrix (Windows) and NICE EnginFrame (Linux) interactive computing environments hosted by MSI.

Stratus Protected Data Cloud

MSI is building a local research compute cloud environment called Stratus ( https://stratus.msi.umn.edu ) , which is designed to store and analyze protected data, such as dbGaP. Stratus is a subscription-based infrastructure as a service that enables users to operate within their own self-service...

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